A Steerable GA Method for Block Erection of Shipbuilding in Virtual Environment

  • Jinsong Bao
  • Qian Wang
  • Aiming Xu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8683)


Solving the dispatch and optimization of block erection of shipbuilding is a complex problem, especially when the spatial constraints are considered. The block erection scheduling problem can be defined as an identical parallel machine scheduling problem with precedence constraints and machine eligibility (PCME) restrictions, as well as limited layout space. An enhanced genetic algorithm (GA) is proposed to find the near-optimal solution, and a few lower bounds. Also, the percentage of the reduced makespan is defined to evaluate the performance of the proposed algorithm. The proposed GA method of steering optimization produces quicker and lesser values of makespan than the RANDOM heuristic algorithm for the collected real instances. It not only allows users to steer a computing towards effective direction and leverages computing, but also is guided by the intelligence of human to get a global view when the users are in immersive environment. The dispatch of block erection to the crane is modeled into a parallel machine scheduling problem with spatial constraints. Meanwhile a 3D layout of block erection is modeled with real size, and an interactive GA optimization is developed to solve this problem with the objective of minimizing makespan.


Steerable Genetic algorithm Scheduling Parallel machines Shipbuilding Virtual environment 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Aho, I., Mäkinen, E.: On a parallel machine scheduling problem with precedence constraints. Journal of Scheduling 9(5), 493–495 (2006)CrossRefzbMATHMathSciNetGoogle Scholar
  2. 2.
    Alcan, P., Başlıgil, H.: An application with non-identical parallel machines using genetic algorithm with the help of fuzzy logic. Proceedings of the World Congress on Engineering 45(1), 272–280 (2011)Google Scholar
  3. 3.
    Caprace, J.D., Petcu, C., Velarde, M., Rigo, P.: Optimization of shipyard space allocation and scheduling using heuristic algorithm. Journals of Marine Science & Technology 18(3), 404–417 (2013)CrossRefGoogle Scholar
  4. 4.
    Gasior, J., Seredynski, F.: Multi-objective Parallel Machines Scheduling for Fault-Tolerant Cloud Systems. In: ICA3PP(1), pp. 247–256 (2013)Google Scholar
  5. 5.
    Klau, G.W., Lesh, N., Marks, J., Mitzenmacher, M.: Human-guided search. Journal of Heuristics 16(3), 289–310 (2010)CrossRefzbMATHGoogle Scholar
  6. 6.
    Klau, G.W., Lesh, N., Marks, J., Mitzenmacher, M., Schafer, G.T.: The HuGS platform: A toolkit for interactive optimization. In: Proceedings of the Working Conference on Advanced Visual Interfaces, pp. 324–330. ACM (May 2002)Google Scholar
  7. 7.
    Lee, J.K., Lee, K.J., Park, H.K., Hong, J.S., Lee, J.S.: Developing scheduling systems for Daewoo shipbuilding: DAS project. European Journal of Operational Research 97(2), 380–395 (1997)CrossRefzbMATHGoogle Scholar
  8. 8.
    Lin, Y., Li, W.: Parallel machine scheduling of machine-dependent jobs with unit-length. European Journal of Operational Research 156(1), 261–266 (2004)CrossRefzbMATHMathSciNetGoogle Scholar
  9. 9.
    Malve, S., Uzsoy, R.: A genetic algorithm for minimizing maximum lateness on parallel identical batch processing machines with dynamic job arrivals and incompatible job families. Computers & Operations Research 34(10), 3016–3028 (2007)CrossRefzbMATHMathSciNetGoogle Scholar
  10. 10.
    Okumoto, Y., Iseki, R.: Optimization of steel plate cutting sequence using the tabu search method. Journal of ship production 21(2), 134–139 (2005)Google Scholar
  11. 11.
    Park, K., Lee, K., Park, S., Kim, S.: Modeling and solving the spatial block scheduling problem in a shipbuilding company. Computers & industrial engineering 30(3), 357–364 (1996)CrossRefMathSciNetGoogle Scholar
  12. 12.
    Ramachandra, G., Elmaghraby, S.E.: Sequencing precedence-related jobs on two machines to minimize the weighted completion time. International Journal of Production Economics 100(1), 44–58 (2006)CrossRefGoogle Scholar
  13. 13.
    Varghese, R., Yoon, D.Y.: Shipbuilding erection network optimization: a TSP method. Journal of ship production 22(3), 139–146 (2006)Google Scholar
  14. 14.
    Yoon, D.Y., Varghese, R.: Looking-forward scheduling approach applied in pre-erection area of a shipyard. Journal of Ship production 23(1), 30–35 (2007)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jinsong Bao
    • 1
  • Qian Wang
    • 1
  • Aiming Xu
    • 1
  1. 1.Shanghai Jiao Tong UniversityShanghaiChina

Personalised recommendations